A decision graph is a way to represent a decision process or a strategy. A decision graph structure is composed of nodes and links in which the leaf nodes represent actions to be taken, the interior nodes represent conditions to be tested on variables, and the paths represent conjunctions of conditions that lead to actions. A node, interior or leaf, can be reached from the root through different paths. The number of links between the root and a node is termed the distance of the node for that path.
A test on a variable is introduced into a decision path only when it is significant in the decision process. As a result, not all variables appear in every path and sometimes same variable appears multiple times in a path. Moreover, variables might appear in different order across different paths. FIG. 1 is an example graph 100 that is unordered and has multiple instances of the same variables in a single path. It has four test variables X, Y, Z and W that can take continuous range of numerical values and leaf variable “A” that can take discrete values A1, A2 and A3. The left most path of the graph 110 contains the test for variable X more than once (X<1 and X<0) so the graph is non-read once. The graph is unordered because two paths have conflicting order of variables. The path in the middle 120 has ordering X→Z→W→Y→A and the path on the right side 130 has ordering X→Z→Y→W→A.